Evaluation of the Aid-Growth Relationship

Presented by Ghassan Baliki and Emiko Nishii

Development Workshop04.11.2010

Outline• Empirical Framework of Rajan and Subramanian (2005) • Potential drawbacks

• How can we understand the Aid-Growth relationship better?

• Aid Effectiveness Literature (AEL): A Meta-Study

• Main Findings and Concluding Remarks

Rajan and Subramanian (2005): What Does theCross-Country Evidence Really Show?

• Endogeneity issues – Aid may depend on level of income

(i.e. donors increase aid inflows based on recipients’ needs)>> Aid can’t be exogenous with respect to growth

• Constructing instruments for Aid is necessary

• Alesina & Dollar (1998)>> Aid is often allocated based on historical &

diplomatic reasons

Rajan and Subramanian (2005): Cont’d

Constructing IV for Aid:

1) Find the share of donor d’s aid allocated to recipient r in year t.

2) Use the predicted share to compute aid to GDP ratio received by country r in year t.

Rajan and Subramanian (2005): Cont’d

• Dependent variable: average annual growth rate of per capita GDP ( 1960-2000, 1970-2000, 1980-2000, 1990-2000)

• The results suggest that with exclusion of outliers, 3 out of 5 cases, the coefficient of Aid is negative, and significant in none.

>> decomposition of Aid is necessary to understand the Aid-Growth relationship better

Rajan and Subramanian (2005): Cont’d

Disaggregate Aid by:

1) Sectors (social, economic and food)

2) Timing of impact (short, and long impact)e.g. whereas food aid should not be expected to affect long-

run growth, social & economic aid should

3) Type of donor (multilateral vs. bilateral)i.e. multilateral aid is less ‘political’ than bilateral aid

>> the results show that no sub-categories have any significant impact

Rajan and Subramanian (2005): Cont’d

• Non-linear & conditional effects of Aid on growth. - Aid effectiveness depends on policy environments?

“aid effectiveness depends on the institutions that restrict appropriation of public funds by rent seeking agents” Hodler (2007)

>> inclusion of policy measures (e.g. CPIA by the World Bank)

- Diminishing return of aid? >> inclusion of aid squared

• Results suggest that in no case, the coefficients are significant.

>> potentially driven by endogeneity and country-specific characteristics

Rajan and Subramanian (2005):Cont’d - the first-difference GMM - the system GMM

>> the results are fragile (e.g. depends on the # of lags or independent variables included, the results change)

First-difference GMM

system GMM

Total aid - and significant - and insignificantShort-impact aid

- and significant - and insignificant

Economic aid + and significant + and significant

Rajan and Subramanian (2005): Cont’d• Quantitative Impact of Aid

Assumption: Mainly, Aid influences growth through increasing public investment.

α=0.35, Y/K=0.45, and β=1 give a suggested coefficient of 0.16.

>> the coefficients for many existing literature are overestimated.

Rajan and Subramanian (2005): Cont’d

• We must pay attention to the potential importance of a previously neglected factors. The importance of understanding ‘Aid influences growth through which channels exactly?’: >> In this context, investigating ‘What’s preventing aid from having a positive impact on growth?’ may be helpful.

Related Literature: - Lensink and Morrissey (1999) “Uncertainty of Aid

Inflows and the Aid-Growth Relationship”

- Rajan and Subramanian (2005) “What Undermines Aid’s Impact on Growth?”

Lensink and Morrissey (1999): “Uncertainty of Aid Inflows and the Aid-Growth Relationship”

• Aim: The paper seeks to find whether uncertainty associated with (volatility of) the level of aid inflows affects the impact of aid on growth.

• Potential impact of Aid on growth with the presence of Uncertainty:

- investors may postpone/cancel investment decisions - Aid is an important component of government

revenues >>volatility of receipts may impact on fiscal behavior, thus growth

Policies/Institutions may be conditional on aid inflows.

Financial Resources Inflows from DAC to Developing Countries

Lensink and Morrissey (1999) Cont’d

• Dependent variable: avg. growth rate of GDP per capita

• Aid=level of Aid

• Construct proxy for uncertainty1) a forecasting equation is estimated (as a first or second-

order autoregressive process, extended with a time trend)

2) calculate the standard deviation of the residuals from the forecasting equation

>> The coefficients on uncertainty are negative and significant.

>> When the uncertainty measure is included Aid becomes significant and positive

Lensink and Morrissey (1999): Cont’dStill some drawbacks………

• By using the cross-country approach, there are possibilities that exogenous factors leading to a bias estimator.

• Almost any explanatory variable could be found to have a significant effect whereas the ‘truth’ is that apparent significance is due to common causalities or spurious regressions >> omitted variable bias still remains.

• Is “growth” a good variable to capture the effectiveness of aid?

Rajan and Subramanian (2005): “What Undermines Aid’s Impact on Growth?”

What’s preventing Aid from having a positive impact on growth?

- The Aid-Competitiveness Approach

• Best way to check aid-effectiveness is to compare ‘fact’ and ‘counter-fact’ >> not possible.

• Instead, check whether labor-intensive industries grow relatively slower in countries with high aid-inflow compare to non-labor- intensive industries.

• This approach allows us to capture 1) within-country differential effects, and 2) country treatment effect to understand the effect of aid.

Rajan and Subramanian (2005): “What Undermines Aid’s Impact on Growth?”

How Aid can influence growth through ‘competitiveness’ channel?

Under the fixed exchange rate:• Aid spent on domestic goods pushes up the price of

recourses that are in limited supply domestically (e.g. skilled worker).

Under the flexible exchange rate:• Aid inflows increase nominal exchange rate, thus reducing

competitiveness.

Rajan and Subramanian (2005): “What Undermines Aid’s Impact on Growth?”

• Strong evidence consistent with aid undermining the competitiveness of the labor-intensive or exporting sectors.

• In countries that receive more aid, labor-intensive and exportable sectors grow slower relative to capital-intensive and non-exportable sectors.

• Aid inflows do cause overvaluation

Are the results compelling?

• Major exports sector for all recipient counties is labor-intensive?

• on balance, whether these adverse competitiveness effects offset any beneficial effects of aid is unclear.

AEL – Doucouliagos and Paldam (2006, 2007a, 2008)▫Do the estimates of the AEL converge to

something we might term 'truth'?

▫Can we identify the main innovations which cause (prevent) convergence?

▫Do biases exist while uncovering the 'truth' about aid effectiveness ?

Three Perennial Problems▫ 1) Priors▫ 2) Data Mining▫ 3)Incentives- Innovation with skepticism- Reliance on independent

replication- and the Reluctance Hypothesis

Absolute Aid Ineffectiveness

Why is it Puzzling?▫“Why would they” vs. “If it is, it must be

rational” → Aid fatigue

▫Marginal Project vs. Financed Project

▫Always via accumulation?

▫No repay means no crowding out

Meta-Analysis•Priors and Biases:

▫Polishing▫Ideology▫Goodness

•Meta Analysis Methodologies:▫Meta-Significance Test (MST)▫Precision-Effect Testing (PET)▫Funnel Asymmetry Test (FAT)

The Three Family Models of AEL

Does Aid Cause Increasing Accumulation?

Large but probably not full crowding effect

A Large Crowding Out

Does Aid Cause Increasing Growth?

•Neoclassical Model:

•Results:▫Decline in variation over time and with

sample size▫More Extreme points▫Average decreasing▫Non-symmetrical funnel around horizontal

axis

Funnel Plot, No Economic Significance!

Aid Growth Effects: Reluctance Trends

Is the Effect of Aid on Growth Conditional?

•Good Policy Model (Burnside and Dollar, 2000):

•The Medicine Model (Lensink and White, 2001):

Conclusion of the Three Meta-Studies